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MIT 18.06SC Linear Algebra, Fall 2011

Publication date: 2011

Usage: Attribution-Noncommercial-Share Alike 3.0

Topics: matrix theory, linear algebra, systems of equations, vector spaces, determinants, eigenvalues, similarity, positive definite matrices, least-squares approximations, stability of differential equations, networks, Fourier transforms, Markov processes

Language: English

This collection contains a group of problem solving videos. Each video is led by a teaching assistant, who works through a particular linear algebra problem to show OCW users how to complete it.

View the complete course at: http://ocw.mit.edu/18-06SCF11

Addeddate: 2011-12-09 16:12:05

Color: color

Identifier: MIT18.06SCF11

Sound: sound

Year: 2011

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ITEM TILE

MPEG4

16.8M

An Interview with Gilbert Strang on Teaching Linear Algebra

18.7M

Inverse Matrices

18.2M

Basis and Dimension

23.8M

Computing the Four Fundamental Subspaces

28.6M

22.0M

Properties of Determinants

18.0M

Least Squares Approximation

20.3M

Powers of a Matrix

41.6M

Differential Equations and exp (At)

19.9M

27.3M

Final Exam Problem Solving

18.3M

Similar Matrices

25.9M

Computing the Singular Value Decomposition

39.7M

Exam #2 Problem Solving

32.8M

Subspaces of Three Dimensional Space

22.2M

Gram-Schmidt Orthogonalization

36.8M

Geometry of Linear Algebra

30.8M

Determinants and Volume

21.3M

LU Decomposition

23.2M

Orthogonal Vectors and Subspaces

26.3M

Markov Matrices

21.8M

Projection into Subspaces

21.0M

Eigenvalues and Eigenvectors

28.2M

Symmetric Matrices and Positive Definiteness

29.1M

Complex Matrices

23.0M

Elimination with Matrices

22.4M

17.2M

An Overview of Key Ideas

27.8M

Graphs and Networks

19.5M

Vector Subspaces

32.6M

28.6M

Exam #3 Problem Solving

27.7M

Change of Basis

28.6M

Positive Definite Matrices and Minima

20.2M

33.0M

Exam #1 Problem Solving

24.0M

Linear Transformations

16.3M

Course Introduction

32.2M

MIT18_06SCF11_Educator_Video_300k.ogv

35.7M

MIT18_06SC_110526_A1_300k.ogv

34.7M

MIT18_06SC_110526_A2_300k.ogv

45.4M

MIT18_06SC_110526_B2_300k.ogv

54.4M

MIT18_06SC_110526_L1_300k.ogv

42.1M

MIT18_06SC_110531_A2_300k.ogv

34.3M

MIT18_06SC_110531_B1_300k.ogv

38.7M

MIT18_06SC_110531_B2_300k.ogv

79.5M

MIT18_06SC_110531_L1_300k.ogv

37.8M

MIT18_06SC_110607_A1_300k.ogv

52.1M

MIT18_06SC_110607_A2_300k.ogv

34.8M

MIT18_06SC_110607_B1_300k.ogv

49.4M

MIT18_06SC_110607_B2_300k.ogv

75.9M

MIT18_06SC_110607_L1_300k.ogv

62.8M

MIT18_06SC_110607_L2_300k.ogv

42.4M

MIT18_06SC_110609_A1_300k.ogv

70.3M

MIT18_06SC_110609_L2_300k.ogv

58.7M

MIT18_06SC_110609_L4_300k.ogv

40.6M

MIT18_06SC_110706_B1_300k.ogv

43.9M

MIT18_06SC_110706_D1_300k.ogv

50.3M

MIT18_06SC_110706_D2_300k.ogv

41.5M

MIT18_06SC_110706_N1_300k.ogv

39.6M

MIT18_06SC_110706_N2_300k.ogv

54.0M

MIT18_06SC_110711_D1_300k.ogv

55.5M

MIT18_06SC_110711_D2_300k.ogv

43.7M

MIT18_06SC_110711_M1_300k.ogv

42.8M

MIT18_06SC_110711_M2_300k.ogv

32.8M

MIT18_06SC_110711_M3_300k.ogv

53.1M

MIT18_06SC_110711_N1_300k.ogv

37.1M

MIT18_06SC_110711_N2_300k.ogv

62.5M

MIT18_06SC_110714_D1_300k.ogv

54.8M

MIT18_06SC_110714_D2_300k.ogv

52.9M

MIT18_06SC_110714_M1_300k.ogv

54.6M

MIT18_06SC_110714_M2_300k.ogv

38.4M

MIT18_06SC_110714_M3_300k.ogv

63.0M

MIT18_06SC_110714_N1_300k.ogv

45.7M

MIT18_06SC_110714_N2_300k.ogv

31.4M

MIT18_06SC_intro_300k.ogv

SUBRIP

9.9K

An Interview with Gilbert Strang on Teaching Linear Algebra

10.1K

Inverse Matrices

10.3K

Basis and Dimension

11.3K

Computing the Four Fundamental Subspaces

14.2K

11.9K

Properties of Determinants

8.5K

Least Squares Approximation

9.3K

Powers of a Matrix

20.0K

Differential Equations and exp (At)

10.4K

14.4K

Final Exam Problem Solving

8.8K

Similar Matrices

10.7K

Computing the Singular Value Decomposition

20.8K

Exam #2 Problem Solving

16.9K

Subspaces of Three Dimensional Space

11.1K

Gram-Schmidt Orthogonalization

17.0K

Geometry of Linear Algebra

15.5K

Determinants and Volume

11.2K

LU Decomposition

10.6K

Orthogonal Vectors and Subspaces

13.3K

Markov Matrices

8.9K

Projection into Subspaces

7.6K

Eigenvalues and Eigenvectors

14.5K

Symmetric Matrices and Positive Definiteness

16.6K

Complex Matrices

12.4K

Elimination with Matrices

11.5K

7.8K

An Overview of Key Ideas

12.1K

Graphs and Networks

8.6K

Vector Subspaces

15.3K

14.6K

Exam #3 Problem Solving

14.5K

Change of Basis

13.9K

Positive Definite Matrices and Minima

8.7K

13.4K

Exam #1 Problem Solving

10.0K

Linear Transformations

8.3K

Course Introduction

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